PITTSBURGH (KDKA) – Scientists say they have developed a new technique for identifying cancer cells in a blood sample more accurately and faster thanks to artificial intelligence.
Researchers at the California NanoSystems Institute at UCLA developed the technique that combines a special microscope with an artificial intelligence algorithm to identify cancerous cells.
Using the new method could reduce the time and energy to diagnose cancer, allowing doctors to treat it more quickly.
The new microscope is called a photonic time stretch microscope, which uses nanosecond-long pulses of light to capture images of hundreds of thousands of cells per second.
Researchers say it works by taking pictures of flowing blood cells, the way a camera uses a flash.
Those images are fed into a computer program which then categorizes the cells different physical features.
Researchers were then able to train a computer program to identify the cancerous cells.
They say the system was at least 17-percent better than using existing analytical tools.
The study was published in the journal Nature Scientific Reports, was led by Barham Jalali, professor and Northrop-Grumman Optoelectronics Chair in electrical engineering; Claire Lifan Chen, a UCLA doctoral student; and Ata Mahjoubfar, a UCLA postdoctoral fellow.
"Each frame is slowed down in time and optically amplified so it can be digitized," Mahjoubfar said in the press release. "This lets us perform fast cell imaging that the artificial intelligence component can distinguish."
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